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Machine Learning in Python and written through Google Colab environment, to predict a particular image using Convolutional Neural Networks (CNN) architecture layer model.

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Welcome to the README of Machine Learning: Image Classification.

The Dataset 📈

This repository uses dataset available here.

The Devs ✒️

This repository is developed as Final Assignment of Belajar Machine Learning untuk Pemula module, a part of Data Science learning path of Dicoding awarded by IDCamp 2023.

The Problems 📝

This repository is focusing on these following bulletpoints:

  • Data split : 60% train and 40% validation
  • Commencing image augmentation
  • Utilizing Image Data Generator
  • Developing sequential model
  • Training duration not more than 30 minutes
  • 85% of minimum accuracy
  • Able to precisely predict loaded image

The Libraries 📚

  • numpy library to carry out numerical computation such as sets, arrays, multidimension matrixes, and vectors
  • pandas library to undergo data processing, analysing, and manipulation using dataframe
  • matplotlib library to perform visualization using plotting
  • os library to execute loading data
  • zipfile library to extract file
  • skicit learn library to split dataset
  • tensorflow library to generate image
  • keras library to displaying image

Copyright © Nicko Arya Dharma 2023 All Rights Reserved

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Machine Learning in Python and written through Google Colab environment, to predict a particular image using Convolutional Neural Networks (CNN) architecture layer model.

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